D1.3 - Algorithms on graphs II

Algorithm for finding the shortest Also known as the ‘Chinese postman’ problem.; Students route around a network, travelling will be expected to use inspection to consider all possible along every edge at least once and pairings of odd nodes. ending at the start vertex.; The (The application of Floyd’s algorithm to the odd nodes is network will have up to four odd not required.) nodes.

Use algorithm for finding the shortest to connect the rule to the data and decision in the question.

This matters because algorithm for finding the shortest determines what can be inferred or chosen; begin with the stated conditions and keep the conclusion tied to the evidence.

Example: apply algorithm for finding the shortest to one small, clearly defined case, show the key step or comparison, and explain the result in words.

Boundary: Algorithm for finding the shortest is not a universal recommendation. Check the syllabus scope, assumptions, units and the limits of the evidence before generalising.

The practical and classical The use of short cuts to improve upper bound is included.; Travelling Salesman problems.; The classical problem for complete graphs satisfying the triangle inequality.

Use practical and classical to connect the rule to the data and decision in the question.

This matters because practical and classical determines what can be inferred or chosen; begin with the stated conditions and keep the conclusion tied to the evidence.

Example: apply practical and classical to one small, clearly defined case, show the key step or comparison, and explain the result in words.

Boundary: Practical and classical is not a universal recommendation. Check the syllabus scope, assumptions, units and the limits of the evidence before generalising.

Determination of upper and lower The conversion of a network into a complete network of bounds using minimum spanning shortest ‘distances’ is included. tree methods.

Use determination of upper and lower to connect the rule to the data and decision in the question.

This matters because determination of upper and lower determines what can be inferred or chosen; begin with the stated conditions and keep the conclusion tied to the evidence.

Example: apply determination of upper and lower to one small, clearly defined case, show the key step or comparison, and explain the result in words.

Boundary: Determination of upper and lower is not a universal recommendation. Check the syllabus scope, assumptions, units and the limits of the evidence before generalising.

The nearest neighbour algorithm.

Use nearest neighbour algorithm to connect the rule to the data and decision in the question.

This matters because nearest neighbour algorithm determines what can be inferred or chosen; begin with the stated conditions and keep the conclusion tied to the evidence.

Example: apply nearest neighbour algorithm to one small, clearly defined case, show the key step or comparison, and explain the result in words.

Boundary: nearest neighbour algorithm is not a universal recommendation. Check the syllabus scope, assumptions, units and the limits of the evidence before generalising.